The ability to perceive and comprehend a traffic situation and to predict the intent of vehicles and road-users in the surrounding of the ego-vehicle is known as situational awareness. Situational awareness for a heavy-duty autonomous vehicle is a critical part of the automation platform and is dependent on the ego-vehicle's field-of-view. But when it comes to the urban scenario, the field-of-view of the ego-vehicle is likely to be affected by occlusion and blind spots caused by infrastructure, moving vehicles, and parked vehicles. This paper proposes a framework to improve situational awareness using set-membership estimation and vehicle-to-everything (V2X) communication. This framework provides safety guarantees and can adapt to dynamically changing scenarios, and is integrated into an existing complex autonomous platform. A detailed description of the framework implementation and real-time results are illustrated in this paper.
翻译:了解和理解交通状况以及预测汽车和道路使用者在自驾驶车辆周围的意图的能力被称为 " 情况意识 " ; 重型自驾驶车辆的情况意识是自动化平台的一个关键部分,取决于自驾驶车辆的视野; 但是,在城市形势下,自驾驶车辆的视野可能受到基础设施、移动车辆和停放车辆造成的隔离和盲点的影响; 本文提出一个框架,利用固定会员估计和车辆到每件车辆之间的通信(V2X)来提高情况意识; 这一框架提供安全保障,能够适应动态变化的情景,并被纳入一个现有的复杂自主平台; 本文详细说明了框架的执行情况和实时结果。